A comparison of mixed frequency approaches for nowcasting Euro area macroeconomic aggregates
License
Access Rights
Cadmus Permanent Link
Full-text via DOI
ISBN
ISSN
0169-2070; 1872-8200
Issue Date
Type of Publication
LC Subject Heading
Other Topic(s)
EUI Research Cluster(s)
Initial version
Published version
Succeeding version
Preceding version
Published version part
Earlier different version
Initial format
Citation
International journal of forecasting, 2014, Vol. 30, No. 3, pp. 554-568
Cite
FORONI, Claudia, MARCELLINO, Massimiliano, A comparison of mixed frequency approaches for nowcasting Euro area macroeconomic aggregates, International journal of forecasting, 2014, Vol. 30, No. 3, pp. 554-568 - https://hdl.handle.net/1814/33956
Abstract
In this paper, we focus on the different methods which have been proposed in the literature to date for dealing with mixed-frequency and ragged-edge datasets: bridge equations, mixed-data sampling (MIDAS), and mixed-frequency VAR (MF-VAR) models. We discuss their performances for nowcasting the quarterly growth rate of the Euro area GDP and its components, using a very large set of monthly indicators. We investigate the behaviors of single indicator models, forecast combinations and factor models, in a pseudo real-time framework. MIDAS with an AR component performs quite well, and outperforms MF-VAR at most horizons. Bridge equations perform well overall. Forecast pooling is superior to most of the single indicator models overall. Pooling information using factor models gives even better results. The best results are obtained for the components for which more economically related monthly indicators are available. Nowcasts of GDP components can then be combined to obtain nowcasts for the total GDP growth.
